Search
552 articles for “intelligent modeling”
-
Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
-
Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
-
Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
-
Smart Glasses Using Ultrasonic Sensor and AI for Blind Person
Abstract: Smart glasses has received considerable attention recently from people around the world. This research paper introduces a pioneering project, 'Smart Glasses Using AI and Ultrasonic Sensor,' aimed at revolutionizing the assistive technology landscape for visually impaired individuals. The project seamlessly integrates advanced hardware, including Raspberry Pi and Node MCU, with an array of sensors and state-of-the-art machine learning techniques, notably the YOLOv5 model. This paper presents a new paradigm in …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 1–9 Read article
-
Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
-
Smart Ways to Manage Waste with AI and IOT: A Review
Abstract: Rapid urban growth and population have led to exponential growth in municipal solid waste over traditional inefficient waste management systems (collection / segregation / disposal). This paper reviews the convergence of Internet-of- Things (IoT) and artificial intelligence (AI), seen as two potential smart techniques to launch smarter waste management. The research reports important applications for AI and IoT in waste classification, waste collection optimization, waste-to-energy as well as smart bin …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 26–31 Read article
-
Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
-
Next-Generation Satellite Remote Sensing: Innovations, Applications, and Future Prospects
Abstract: Advances in satellite remote sensing have revolutionized our ability to monitor, analyze, and understand the Earth's environment across various scales. Over the past few decades, the field has seen remarkable progress in sensor technology, data processing techniques, and analytical methodologies. Modern satellites now provide high-resolution imagery and multi-spectral data, enabling enhanced monitoring of land cover, atmospheric conditions, oceanic dynamics, and natural disasters. These advancements have facilitated improvements in climate change …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 37–62 Read article
-
AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
-
The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
-
Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
-
AI Activity to Enhance Productivity, Creativity, and Sustainable Development of AI in Healthcare
Abstract: The application of artificial intelligence (AI) in healthcare is revolutionizing the industry by fostering both productivity and creative approaches to patient care and medical research. This study explores how artificial intelligence (AI) is reshaping healthcare by streamlining workflows, improving diagnostic precision, and supporting personalized treatment plans. AI-powered technologies are reshaping the way medical professionals approach patient care, providing tools that not only automate routine administrative and clinical tasks but also …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 21–29 Read article
-
Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
-
Website Usability Using AI
Abstract: This article introduces a comprehensive framework that leverages artificial intelligence (AI), automated tools, and APIs to enhance the evaluation of website usability. The proposed framework integrates AI-driven models with traditional usability assessment techniques to create a more dynamic and effective evaluation process. Specifically, it utilizes Google Lighthouse to conduct in-depth audits on website performance, search engine optimization (SEO), and accessibility. Additionally, chatbot APIs are incorporated to gather real-time user feedback, …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 19–27 Read article
-
Identification of Brain Stroke Using Artificial Intelligence
Abstract: Globally, strokes are the primary cause of disability and mortality. Recently, machine learning (ML) and deep learning (DL) have been employed by artificial intelligence algorithms as effective stroke diagnosing techniques. These days, machine learning and data mining technologies are used in the construction of the main models. We have used five machine learning algorithms to determine if a stroke has occurred or is likely to occur based on a patient’s …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
-
A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
-
Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
-
Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
-
Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article